No abstract

Like many species, movement patterns of southern elephant seals (Mirounga leonina) are being influenced by long‐term environmental change. These seals migrate up to 4,000 km from their breeding colonies, foraging for months in a variety of Southern Ocean habitats. Understanding how movement patterns vary with environmental features and how these relationships differ among individuals employing different foraging strategies can provide insight into foraging performance at a population level. We apply new fast‐estimation tools to fit mixed effects within a random walk movement model, rapidly inferring among‐individual variability in southern elephant seal environment–movement relationships. We found that seals making foraging trips to the sea ice on or near the Antarctic continental shelf consistently reduced speed and directionality (move persistence) with increasing sea‐ice coverage but had variable responses to chlorophyll a concentration, whereas seals foraging in the open ocean reduced move persistence in regions where circumpolar deep water shoaled. Given future climate scenarios, open‐ocean foragers may encounter more productive habitat but sea‐ice foragers may see reduced habitat availability. Our approach is scalable to large telemetry data sets and allows flexible combinations of mixed effects to be evaluated via model selection, thereby illuminating the ecological context of animal movements that underlie habitat usage.

A fundamental goal in animal ecology is to quantify how environmental (and other) factors influence individual movement, as this is key to understanding responsiveness of populations to future change. However, quantitative interpretation of individual-based telemetry data is hampered by the complexity of, and error within, these multi-dimensional data. Here, we present an integrative hierarchical Bayesian state-space modelling approach where, for the first time, the mechanistic process model for the movement state of animals directly incorporates both environmental and other behavioural information, and observation and process model parameters are estimated within a single model. When applied to a migratory marine predator, the southern elephant seal (Mirounga leonina), we find the switch from directed to resident movement state was associated with colder water temperatures, relatively short dive bottom time and rapid descent rates. The approach presented here can have widespread utility for quantifying movement-behaviour (diving or other)-environment relationships across species and systems.

Abstract. In animal ecology, a question of key interest for aquatic species is how changes in movement behavior are related in the horizontal and vertical dimensions when individuals forage. Alternative theoretical models and inconsistent empirical findings mean that this question remains unresolved. Here we tested expectations by incorporating the vertical dimension (dive information) when predicting switching between movement states (''resident'' or ''directed'') within a state-space model. We integrated telemetry-based tracking and diving data available for four seal species (southern elephant, Weddell, antarctic fur, and crabeater) in East Antarctica. Where possible, we included dive variables derived from the relationships between (1) dive duration and depth (as a measure of effort), and (2) dive duration and the postdive surface interval (as a physiological measure of cost). Our results varied within and across species, but there was a general tendency for the probability of switching into ''resident'' state to be positively associated with shorter dive durations (for a given depth) and longer postdive surface intervals (for a given dive duration). Our results add to a growing body of literature suggesting that simplistic interpretations of optimal foraging theory based only on horizontal movements do not directly translate into the vertical dimension in dynamic marine environments. Analyses that incorporate at least two dimensions can test more sophisticated models of foraging behavior.

Abstract. The behavior of colony-based marine predators is the focus of much research globally. Large telemetry and tracking data sets have been collected for this group of animals, and are accompanied by many empirical studies that seek to segment tracks in some useful way, as well as theoretical studies of optimal foraging strategies. However, relatively few studies have detailed statistical methods for inferring behaviors in central place foraging trips. In this paper we describe an approach based on hidden Markov models, which splits foraging trips into segments labeled as "outbound", "search", "forage", and "inbound". By structuring the hidden Markov model transition matrix appropriately, the model naturally handles the sequence of behaviors within a foraging trip. Additionally, by structuring the model in this way, we are able to develop realistic simulations from the fitted model. We demonstrate our approach on data from southern elephant seals (Mirounga leonina) tagged on Kerguelen Island in the Southern Ocean. We discuss the differences between our 4-state model and the widely used 2-state model, and the advantages and disadvantages of employing a more complex model.

Summary 1.Seasonal long-distance migrations are often expected to be related to resource distribution, and foraging theory predicts that animals should spend more time in areas with relatively richer resources. Yet for highly migratory marine species, data on feeding success are difficult to obtain. We analysed the temporal feeding patterns of wild juvenile southern bluefin tuna from visceral warming patterns recorded by archival tags implanted within the body cavity. 2. Data collected during 1998-2000 totalled 6221 days, with individual time series ( n = 19) varying from 141 to 496 days. These data span an annual migration circuit including a coastal summer residency within Australian waters and subsequent migration into the temperate south Indian Ocean. 3. Individual fish recommenced feeding between 5 and 38 days after tagging, and feeding events ( n = 5194) were subsequently identified on 76·3 ± 5·8% of days giving a mean estimated daily intake of 0·75 ± 0·05 kg. 4. The number of feeding events varied significantly with time of day with the greatest number occurring around dawn (58·2 ± 8·0%). Night feeding, although rare (5·7 ± 1·3%), was linked to the full moon quarter. Southern bluefin tuna foraged in ambient water temperatures ranging from 4·9 ° C to 22·9 ° C and depths ranging from the surface to 672 m, with different targeting strategies evident between seasons. 5. No clear relationship was found between feeding success and time spent within an area. This was primarily due to high individual variability, with both positive and negative relationships observed at all spatial scales examined (grid ranges of 2 × 2 ° to 10 × 10 ° ). Assuming feeding success is proportional to forage density, our data do not support the hypothesis that these predators concentrate their activity in areas of higher resource availability. 6. Multiple-day fasting periods were recorded by most individuals. The majority of these (87·8%) occurred during periods of apparent residency within warmer waters (sea surface temperature > 15 ° C) at the northern edge of the observed migratory range. These previously undocumented nonfeeding periods may indicate alternative motivations for residency. 7. Our results demonstrate the importance of obtaining information on feeding when interpreting habitat utilization from individual animal tracks.

Humpback whale (Megaptera novaeangliae) populations typically undertake seasonal migrations, spending winters in low latitude breeding grounds and summers foraging in high latitude feeding grounds. Until recently, a broad scale understanding of whale movement has been derived from whaling records, Discovery marks, photo identification and genetic analyses. However, with advances in satellite tagging technology and concurrent development of analytical methodologies we can now detail finer scale humpback whale movement, infer behavioural context and examine how these animals interact with their physical environment. Here we describe the temporal and spatial characteristics of migration along the east Australian seaboard and into the Southern Ocean by 30 humpback whales satellite tagged over three consecutive austral summers. We characterise the putative Antarctic feeding grounds and identify supplemental foraging within temperate, migratory corridors. We demonstrate that Antarctic foraging habitat is associated with the marginal ice zone, with key predictors of inferred foraging behaviour including distance from the ice edge, ice melt rate and variability in ice concentration two months prior to arrival. We discuss the highly variable ice season within the putative foraging habitat and the implications that this and other environmental factors may have on the continued strong recovery of this humpback whale population.

The massive number of seabirds (penguins and procellariiformes) and marine mammals (cetaceans and pinnipeds) -referred to here as top predators -is one of the most iconic components of the Antarctic and Southern Ocean. They play an important role as highly mobile consumers, structuring and connecting pelagic marine food webs and are widely studied relative to other taxa. Many birds and mammals establish dense breeding colonies or use haul-out sites, making them relatively easy to study. Cetaceans, however, spend their lives at sea and thus aspects of their life cycle are more complicated to monitor and study. Nevertheless, they all feed at sea and their reproductive success depends on the food availability in the marine environment, hence they are considered useful indicators of the state of the marine resources. In general, top predators have large body sizes that allow for instrumentation with miniature datarecording or transmitting devices to monitor their activities at sea. Development of scientific techniques to study reproduction and foraging of top predators has led to substantial scientific literature on their population trends, key biological parameters, migratory patterns, foraging and feeding ecology, and linkages with atmospheric or oceanographic dynamics, for a number of species and regions. We briefly summarize